The presence of automated-agents on computer networks is becoming common practice for use in conducting repetitive tasks that bombard websites, platforms and system resources. Web scraping, data extraction, indexing and the like are common place techniques for mining information from websites using programs that simulate human-user interaction over a network. A website hosted on server receives traffic or “hits” each time it is accessed by a user, whether that is a human-user or an automated-agent and each webpage associated with the website contains information that is capable of being viewed and used by the human-user and the automated-agent. Servers are increasingly receiving website traffic from these automated-agents, where sometimes upwards of 50-80% of hits are coming from automated-agents. As automated-agent traffic requires central processing unit processing and general use of computing resources in the same way human-user traffic does, resource capacity is increased by each hit received from an automated-agent and bandwidth can be consumed by each additional server hit causing delay and failure for the human-user. Various technical measures and practices exist for excluding or hindering automated-agents from accessing website content by implementing techniques such as blocking an Internet protocol (IP) addresses, disabling web services, blocking automated-agents based on excessive traffic monitoring, attempting to learn automated-agent behavior, implementing reverse Turing test, using Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) or other human interaction proofs. Conventional techniques, however, are often prone to misapplication, such as by inhibiting legitimate access, thereby causing a poor user experience.